Collaborative Research: CyberTraining: Implementation: Medium: Cyberinfrastructure Training and Education for Leveraging Advanced Electron Microscopy in Materials Science

The use of modern computing and data infrastructure is critical to harnessing the full potential of instruments, data, and tools offered by state-of-the-art laboratory facilities, but many scientists do not have the necessary knowledge of data management, scientific programming skills, or the ability to use computing resources to bring them to bear for data analysis, leading to new discoveries. This project - CITEAM - addresses the gap by developing an innovative training program targeting the materials science research community that relies on advanced microscopes for research and needs to process and manage large data volumes to make fundamental advances in materials science. CITEAM provides training for microscope data processing, the use of Artificial Intelligence methods in data analysis, and effective data management, thereby reducing time-to-science. The project helps researchers in overcoming challenges in handling large-scale datasets and utilizing novel computing methods and resources. The project increases computing skills, awareness, and literacy for researchers with limited computing expertise, thereby accelerating the scientific innovations in materials science. The CITEAM project brings together a team of researchers with expertise in cyberinfrastructure (CI) as well as in imaging-enabled materials science to develop an innovative training program targeting the materials science community that relies on advanced microscopes (e.g. Transmission Electron Microscopes (TEM)) for research. This project aims at optimizing return on a state-of-the-art investment in physical infrastructure - a new aberration-corrected Transmission/Scanning Electron Microscope (AC TEM/STEM) at UMD. The training program covers several relevant thematic areas - TEM instrument software, image analysis, scientific computing, application of AI in TEM image and data analysis, diffraction and spectroscopy data analysis, distributed computing for microscope data processing, data curation, and FAIR principles. The training program includes an additional element of "training the trainers" by exposing the research facilitators and laboratory staff scientists to advanced CI topics, empowering them to guide others and innovate in the use of CI for materials science. Training is offered for both users and trainers in a multitude of modalities to promote efficient learning - self-paced modules, video lectures, templates and catalogs, office hours, training sessions at annual CITEAM Users' workshop, and tutorials at domain science conferences. CITEAM promotes community building by developing a coordination network comprising similar imaging laboratories, different domain science communities that use advanced microscopes, and experts from national CI resource providers. The CITEAM coordination network helps in adapting and disseminating training materials beyond the participating institutions, ensuring both scalability and sustainability of the program. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.